Presenter Information

Mentor 1

Derek Riley

Location

Union Wisconsin Room

Start Date

24-4-2015 2:30 PM

End Date

24-4-2015 3:45 PM

Description

Throughout the world, automobile parking space is a resource that is often scarce due to the popularity of automobiles in urban areas. One strategy to limit parking congestion uses parking permits for general lots, but a permit does not guarantee that a given spot will be available at all times. If a spot is not guaranteed, this means that the driver has to spend time in addition to fuel looking for a spot, which could lead to lateness as well as additional air pollution. Improving access to real-time parking availability information has the potential to improve lot utility, energy efficiency, and time savings. Real-time parking information is a valuable commodity in situations where alternative parking locations are available. A survey showed that out of over 480 drivers, 30% changed their intended parking destination after seeing road signs indicating open parking elsewhere. The ability to access information about the availability of spaces in parking lots can change rapidly, so it is ideal to provide this information on a mobile phone application. The increased availability of parking information could even help drivers decide whether to use their own car or find another method of transportation such as the bus or a bike. In this presentation, we introduce a prototype parking monitoring system that uses crowdsourcing and mobile phone sensors to provide more reliable parking availability information for users to find parking in a faster, more efficient manner. A mobile phone app uses GPS to determine the users’ location and prompts them to vote to help determine the congestion of the lot. If the user chooses not to vote, the app will continue to track their GPS location to determine whether they are leaving or entering the lot and what specific zone of the lot they are in using vector mapping. All crowdsourced information is combined in an algorithm to provide a prediction of the fullness of each zone of the parking lot. Our app presents a color coded live map that indicates parking lot fullness status. To reduce the influence of crowdsourcing data manipulation, expert data is also collected by an authority figure such as parking officials or the police department. These authority figures can use a hidden feature on our app to directly insert reliable data to improve the overall quality of data gathered. The expert data overrides any crowdsourced data to ensure the most reliable information is provided to the users.

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Throughout the world, automobile parking space is a resource that is often scarce due to the popularity of automobiles in urban areas. One strategy to limit parking congestion uses parking permits for general lots, but a permit does not guarantee that a given spot will be available at all times. If a spot is not guaranteed, this means that the driver has to spend time in addition to fuel looking for a spot, which could lead to lateness as well as additional air pollution. Improving access to real-time parking availability information has the potential to improve lot utility, energy efficiency, and time savings. Real-time parking information is a valuable commodity in situations where alternative parking locations are available. A survey showed that out of over 480 drivers, 30% changed their intended parking destination after seeing road signs indicating open parking elsewhere. The ability to access information about the availability of spaces in parking lots can change rapidly, so it is ideal to provide this information on a mobile phone application. The increased availability of parking information could even help drivers decide whether to use their own car or find another method of transportation such as the bus or a bike. In this presentation, we introduce a prototype parking monitoring system that uses crowdsourcing and mobile phone sensors to provide more reliable parking availability information for users to find parking in a faster, more efficient manner. A mobile phone app uses GPS to determine the users’ location and prompts them to vote to help determine the congestion of the lot. If the user chooses not to vote, the app will continue to track their GPS location to determine whether they are leaving or entering the lot and what specific zone of the lot they are in using vector mapping. All crowdsourced information is combined in an algorithm to provide a prediction of the fullness of each zone of the parking lot. Our app presents a color coded live map that indicates parking lot fullness status. To reduce the influence of crowdsourcing data manipulation, expert data is also collected by an authority figure such as parking officials or the police department. These authority figures can use a hidden feature on our app to directly insert reliable data to improve the overall quality of data gathered. The expert data overrides any crowdsourced data to ensure the most reliable information is provided to the users.